United States Army Combat Capabilities Development Command Soldier Center, Natick, MA 01760, USA.
Center for Applied Brain and Cognitive Sciences, Medford, MA 02155, USA.
Mil Med. 2023 Jul 22;188(7-8):e2275-e2283. doi: 10.1093/milmed/usad002.
Personnel engaged in high-stakes occupations, such as military personnel, law enforcement, and emergency first responders, must sustain performance through a range of environmental stressors. To maximize the effectiveness of military personnel, an a priori understanding of traits can help predict their physical and cognitive performance under stress and adversity. This work developed and assessed a suite of measures that have the potential to predict performance during operational scenarios. These measures were designed to characterize four specific trait-based domains: cognitive, health, physical, and social-emotional.
One hundred and ninety-one active duty U.S. Army soldiers completed interleaved questionnaire-based, seated task-based, and physical task-based measures over a period of 3-5 days. Redundancy analysis, dimensionality reduction, and network analyses revealed several patterns of interest.
First, unique variable analysis revealed a minimally redundant battery of instruments. Second, principal component analysis showed that metrics tended to cluster together in three to five components within each domain. Finally, analyses of cross-domain associations using network analysis illustrated that cognitive, health, physical, and social-emotional domains showed strong construct solidarity.
The present battery of metrics presents a fieldable toolkit that may be used to predict operational performance that can be clustered into separate components or used independently. It will aid predictive algorithm development aimed to identify critical predictors of individual military personnel and small-unit performance outcomes.
从事高风险职业的人员，如军人、执法人员和紧急救援人员，必须在各种环境压力下保持工作表现。为了最大限度地提高军人的效率，可以预先了解他们的特点，以帮助预测他们在压力和逆境下的身体和认知表现。这项工作开发并评估了一系列有潜力预测作战场景中表现的措施。这些措施旨在描述四个特定的基于特质的领域：认知、健康、身体和社会情感。
191 名现役美国陆军士兵在 3-5 天的时间内完成了交错的问卷调查、坐姿任务和身体任务测量。冗余分析、降维分析和网络分析揭示了一些有趣的模式。
首先，独特变量分析显示出一个最小冗余的仪器电池。其次，主成分分析表明，在每个领域内，指标往往在三到五个组件中聚集在一起。最后，使用网络分析对跨领域关联的分析表明，认知、健康、身体和社会情感领域表现出强烈的结构一致性。
本套指标提供了一个可用于预测作战表现的可行工具包，可分为单独的组件使用或独立使用。它将有助于开发预测算法，以确定个体军人和小单位绩效结果的关键预测因素。
